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Proposal Defence
Proposal Defence
Proposal Defence
Proposal Defence
Proposal Defence
Proposal Defence
Proposal Defence
Proposal Defence
Proposal Defence
Proposal Defence
Proposal Defence
Proposal Defence
Proposal Defence
Proposal Defence
Proposal Defence
Proposal Defence
Proposal Defence
Proposal Defence
Proposal Defence
Proposal Defence
Proposal Defence
Proposal Defence
Proposal Defence
Proposal Defence
Proposal Defence
Proposal Defence
Proposal Defence
Proposal Defence
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Proposal Defence
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Proposal Defence

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This is my masters proposal defence presentation materials.

This is my masters proposal defence presentation materials.

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  • 1. Bipin Upadhyaya M.Sc (Information Systems) Distributed Information Systems Lab Kookmin University Seoul
  • 2.  Continued growth of Internet Services  Search engines, web mail systems, social networks, blogging platform, file sharing systems.  Many use publish-subscribe paradigm  Facebook, YouTube etc  Scaling via geographic distribution of infrastructure.  Moving around large sets of data.
  • 3. What is a Social Network Service?  A social network service focuses on the building and verifying of online social networks for communities of people who share interests and activities, or who are interested in exploring the interests and activities of others, and which necessitates the use of software. Most services are primarily web based and provide a collection of various ways for users to interact, such as • chat, • messaging, • email, • video, • voice chat, • file sharing, • blogging, • discussion groups, and so on.
  • 4.  My interest in particularly in social networks.  Issues: ▪ With existence of so many social networks how can you get connected with all your friends. (people are dispersed in different social networks owned by different providers). ▪ How to have ownership on the data you have created. ▪ Privacy ▪ How to overcome privacy issues. ▪ What kind of Publish-subscribe systems that takes the advantage of geographical proximity and common friends for information dissemination.
  • 5. What are the othe Information that we can get Profiles Activities Group
  • 6.  Terms of service (TOS) in the end user license agreement (EULA) are in fact rather ambiguous:  "Profile information is used by Facebook primarily to be presented back to and edited by you when you access the service and to be presented to others permitted to view that information by your privacy settings. … Facebook may use information in your profile without identifying you as an individual to third parties. . . . We believe this benefits you” (Facebook 2009).
  • 7.  None of OSN provides you with the capability of exporting your profiles and files users’ have uploaded.  You lose your content with deactivation of account.  OSN acts like the islands without interpretability.
  • 8. Account deactivation process in FB
  • 9. What about my content Account deactivation process in FB
  • 10. Showing the query resolved by Overall System Architecture for P2P involving different site
  • 11. Blogs tag Picture Total ownership of data to Bookmarks FOAF the user Profile Videos Each data is semantically rich Private Cloud specifying to which public clouds it is targeted to OpenID OAuth Opensocial Service Access Control Public clouds Instead of uploading data to specific sites to be shared by the user. User can give the authorization at fine granularity. Making the data semantically rich allows semantic queries to be targeted to the private cloud.
  • 12.  Mainly two initiative for creating Social networks in P2P networks.Still in primilary phase of research.  PeerSoN [Ref 2] – (Implemented DHT) ▪ nodes do not monitor the status of their friends constantly, they look up their friends when they want new information .  Tribler [Ref 1] ▪ Is P2P networks which research is going on to make it P2P for social networks.
  • 13.  To get the knowledge about communities and the structure of social networks we tried to mine OSN [facebook]. Number of Nodes Crawled 7094 Average number of Friends ~404 Number of clusters 13
  • 14.  We often forget that computer networks are put in place to support human networks— person-to-person exchanges of information, knowledge, ideas, opinions, insights, and advice.  Generally friends subscribe to your feeds and you subscribe to your friends feed.
  • 15.  Overlay structure based on Community based and network locality might be helpful for information dissemination between friends.
  • 16.  Social Aware Overlay  Exploit community and network proximity using Bloom filter and network coordinates  Discovering new nodes via gossips.  Use the dissemination of Tree approach  Based on network locality.  Pull and push of updates
  • 17.  Nodes try to cluster on the basis of community they belong.  If they nodes is associated to more than one community. It moves to the super peer of the community where is maximum friends belongs.
  • 18. P Publisher selects three children based on proximity and community X Y Z A B C M I am occupied you can contact my child <a,b,c> Based on the proximity chooses one among Based on the proximity <y,z,a,b,c> chooses one among <x,y,z> Join as child or Contact M I am occupied you can contact my child <x,y,z> Wants to subscribe to the content of P
  • 19. Join child or contact [O,M] Z O M X N B F What B knows is its parents till root parent  Z  N
  • 20. When two nodes become friends their exchange public keys Exchange public keys When node P wants to post some message to node B. If B is alive then P can send directly to B
  • 21. If B is dead, P calculates the proximity function of B. Then transmits the message encrypted with the public key of node B to all the nodes within that range of B. Asynchronous messaging is one of the challenging job in P2P Infrastructure. PeerSON uses on of the node in DHT to provide asynchronous message.
  • 22.  Here the term proximity which may sound a little bit ambiguous. Proximity here is the function of distance between the nodes and similarity between the subscription feeds. Proximity=>function ( distance between nodes, similarity between the subscription feeds)
  • 23.  Publish subscribe system based on  Structured P2P  Unstructured P2P
  • 24.  Structured P2P  While conceptually simple. It has some problems: ▪ The rendezvous peers may be chosen from non-groups (because nodes are chosen by hash of id) which obviously present unnatural trust relationship between the group and rendezvous peer. ▪ Rendezvous peer can become hotspots. [ FedTree (Pastry based), Meghdoot (CAN DHT)]
  • 25.  Sub-2-Sub: self-Organizing Content Based Publish Subscribe for Dynamic Large Scale Collaborative Networks.  Relies in epidemic protocol  Peers constantly exchange subscription information to get clustered around similar peers.  SUB-SUB forms an unstructured overlay network in which each peer is associated with a single subscription.  Multiple subscriptions are handled by running multiple virtual peer on the single physical node, each virtual peer maintaining its own set of links.
  • 26.  Quasar: A probabilistic Publish-subscribe for social networks.(Bernard Wong and Saikat Guha, Cornell University)  A scalable P2P publish subscribe system that caters to the specific needs of social networks.  It explores new point in publish-subscribe design that uses a combination of proactive dissemination of aggregated routing vectors together with directed walks to provide an efficient any cast primitive for finding nearby group members.
  • 27.  Quasar: A probabilistic Publish-subscribe for social networks.(Bernard Wong and Saikat Guha, Cornell University)  A scalable P2P publish subscribe system that caters to the specific needs of social networks.  It explores new point in publish-subscribe design that uses a combination of proactive dissemination of aggregated routing vectors together with directed walks to provide an efficient any cast primitive for finding nearby group members.
  • 28. Peer A wants to send a wall message to Peer B while PeerB has no active location [Ref. 2]
  • 29. Is P2P Infrastructure is OK for Social networks ??? [Ref. 6] [Ref. 6 ]
  • 30. Source : http://en.wikipedia.org/wiki/Bloom_filter
  • 31. p J. A. Pouwelse, P. Garbacki, J.Wang, A. Bakker, J. Yang, A. Iosup, D. H. J. Epema, M. Reinders, M. R. van Steen and H. J. Sips TRIBLER: a social-based peer-to-peer system r Sonja Buchegger, Doris Schiöberg, Le Hung Vu, Anwitaman Datta. PeerSoN: P2P Social Networking - Early Experiences and Insights. In Proceedings of SocialNets 2009, The 2nd Workshop on Social Network Systems, Nuernberg, Germany, March 31, 2009
  • 32. ¬ Bloom Filters - the math : pages.cs.wisc.edu/~cao/papers/summary- cache/node8.html u Frank Dabek, Russ Cox, Frans Kaashoek, Robert Morris Vivaldi: A Decentralized Network Coordinate System m Alan Mislove, Krishna P. Gummadi, Peter Druschel Exploiting Social Networks for Internet Search l Mema Roussopoulos, Mary Baker, David S. H. Rosenthal, TJ Giuli, Petros Maniatis, Jeff Mogul P2P or Not 2 P2P? ? Bipin Upadhyaya, Eunmi Choi Social Overlay: P2P Infrastructure for Social Networks
  • 33. l Dan Sandler ,Alan Mislove, Ansley Post ,Peter Druschel FeedTree: Sharing Web micronews with peer-to-peer event notification r Abhishek Gupta , Ozgur D. Sahin , Divyakant Agrawal and Amr El Abbadi Meghdoot: Content- Based Publish/Subscribe over P2P Networks

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